Comparative genomic landscape of lower-grade glioma and glioblastoma

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.


Introduction
Gliomas are the most common malignant brain tumors in the central nervous system (CNS) [1].Gliomas are classified into grades I to IV by the World Health Organization (WHO), mainly based on histology and malignancy [2].Recently, molecular characteristics have been added as an important criterion in the revised classification system [3,4].The traditional treatment for glioma includes surgical resection, radiotherapy, and chemotherapy based on temozolomide (TMZ) [5].These treatment leads to a better prognosis, especially grades II and III (LGG, with median survival time of more than 7 years) [6].However, glioblastoma (GBM, WHO IV) still has poor prognosis (with the 5-year survival rate of 5.8%) [7].
Isocitrate dehydrogenase (IDH) mutations are one of the most critical molecular markers affecting the diagnosis, prognosis and treatment of gliomas.In gliomas, IDH1 R132H is the most common mutation and the mutation is associated with slower progression and better prognosis.IDH1 mutations occur in over 70% of LGG and GBM that progress from LGG and IDH2 mutation occur in less than 5% in gliomas [8].2021 WHO classification systems of CNS includes three types of gliomas: IDH-mutant astrocytoma, IDH-mutant and 1p/19q-codeleted oligodendroglioma and IDH-wildtype GBM [4].More and more molecular markers have been proven to play a crucial role in the classification, grading, prognosis, and treatment of gliomas.For example, IDH-wildtype astrocytic glioma carrying TERT promoter (TERTp) mutation, EGFR amplification, as well as gain-of-chromosome 7 and loss-of-chromosome 10 (+7/-10) are classified as GBM [4].Although many studies have revealed the genomic landscape of gliomas based on Western/European populations predominantly, comparative genomic characteristics of LGG and GBM are yet to be displayed in Chinese patients [9][10][11].Considering the impact of genetic backgrounds on the prognosis of gliomas and a lack of comparative genomics of LGG and GBM in the Chinese population, further comparison of the genomic characteristics between LGG and GBM in the Chinese population is essential.Here, we aim to analyze and compare genomic characteristics of 16 LGG and 35 GBM cases to explore both shared and grade-specific genomics of gliomas in Chinese patients, and thus offering new insight into potential molecular signatures and treatment targets.

Selection of patients with gliomas and sample collection
Tumor tissues were obtained from 51 patients with primary gliomas from January 6, 2019 to July 1, 2020 in Liaocheng People's Hospital and normal blood samples data was obtained from another study of our group [12].These patients were histologically diagnosed with gliomas and underwent surgical resection.According to histopathological diagnosis, tumors were classified as grades II to IV.This study was approved by the medical ethics committee of Liaocheng People's Hospital (No: 2019203, 6 January 2019) and strictly followed the guidelines of the Declaration of Helsinki.All involved patients had signed informed consent for participating in this study.Genomic DNA (gDNA) was extracted from fresh frozen tissues and peripheral blood samples using QIAamp DNA Mini Kit (Qiagen, Hilden, Germany).The quality and quantity of gDNA was analyzed by NanoDrop 1000 (Thermo Scientific, Wilmington, USA) and Qubit 3.0 Fluorometer (Life Technologies, Carlsbad, USA).
The whole exome was captured by SureSelect Human All Exon V6 Probes (Agilent, Santa Clara, USA) according to the manufacturer's protocol.The qualified libraries were sequenced with Nextseq CN500 platform (Illumina, San Diego, USA) for 2×76 bp paired-end sequencing.

CNVs analysis
CNVkit was used to analysis CNVs with default parameter settings [22].Peripheral bloodderived germline DNA samples of 30 healthy subjects were used as normal references for calculating tumor CNVs, which were generated using the same sequencing method and analysis strategy.CNVs were reported if the log2 (CN) was above 1.5 or below 0.5.Then, GISTIC2.0 was used to identify regions of significantly recurring gains or losses [23].q-values were calculated from p-values of respective genomic regions determined by permutation test.Regions with a q < 0.25 were considered as significantly recurring gains or losses.

Statistical analysis
Genetic mutations between LGG and GBM were compared with Fisher's exact tests or Chisquare tests.2-tailed p < 0.05 was considered significant.Kaplan-Meier estimate was illustrated for survival analysis, and log-rank test was used to determine the difference between two groups.The statistical analysis was performed using SPSS (Version23.0,Chicago, USA) or R v3.6.1 software.

Clinical characteristics of patients with gliomas
Totally, 51 patients with gliomas, including 16 LGG and 35 GBM, were enrolled in this investigation (Table 2 and S1

Mutational landscape of LGG and GBM patients
The LGG and GBM shared 53 mutated genes, while 1800 and 3846 uniquely mutations were identified in LGG and GBM, respectively (S1D Fig) .To demonstrate potential grade

CNVs in LGG and GBM
CNVs were analyzed by GISTIC2.0 in the LGG and GBM groups.We identified 6 significantly recurrent amplification regions (q < 0.

Enrichment analysis and oncogenic signaling pathways
To understand the biological distributions of the frequently altered genes, we performed KEGG and GO analyses.KEGG analysis revealed that the frequently altered genes were highly enriched in "pathway in cancer" (Fig 4A).GO analysis indicated that mutated genes were mainly involved in replicative senescence and positive regulation of pri−miRNA transcription from RNA polymerase II promoter in biological processes ( To compare oncogenic signaling pathways by genetic variations, we analyzed mutations and CNVs in LGG and GBM.Notably, TP53 (70.59%),RTK/RAS (37.25%),PI3K (33.33%),HIPPO (31.37%), and NOTCH (25.49%) pathways were frequently altered in gliomas.However, NRF2 and TGFB related genes were not found (Fig 5A).The most frequently mutated gene in the TP53 signaling pathway was TP53.There were differences in oncogenic signaling pathways between LGG and GBM.Interestingly, alterations in RTK/RAS (50% LGG vs.

Discussion
In this study, we performed WES to compare molecular characteristics between 16 LGG with 35 GBM patients in the Chinese population.We have highlighted significant differences in genetic landscapes between LGG and GBM.
The most frequently mutated genes were TP53, TERT, ATRX, EFGLAM, and IDH1 in 51 Chinese patients with gliomas.Except for EFGLAM, the other genes were biomarkers for gliomas [9,[33][34][35].EGFLAM was related to poor prognosis in GBM as previously described [36].Notably, mutations of IDH1 and PCDHGA10 were significantly different between LGG and GBM.IDH1 mutation (c.G395A; p.R132H) was enriched in LGG and patients with IDH1 mutation had better long-term survival.IDH mutations were identified in LGG and secondary GBM, as an important biomarker for longer OS in LGG [37].By contrast, PCDHGA10 mutation (c.A265G; p.I89V) was significantly enriched in GBM but not in LGG (22.86% vs. 0%).In addition, PCDHGA10 mutation correlated with shorter OS time.PCDHGA10 might be a potential biomarker for prognosis in gliomas.PCDHGA10 mutation (c.A265G; p.I89V) has not been reported to be associated with gliomas, which has been reported in other tumors (bladder cancer, gastric adenomas, and gastrointestinal stromal tumors) [38][39][40].PCDHGA10 other mutations (such as c.G1765A, p.G589S; c.A395G/T, D132G/V) have been reported in astrocytoma grade IV [41,42].PCDHGA10 mutational frequency was low in the TCGA GBM (0.8%, 3/374) and cBioPortal GBM (1.01%, 4/397).PCDHGA10 is a member of Pcdh-γ gene clusters.There has been accumulating evidence that members of PCDH family act as tumor suppressor genes in several types of cancer [43][44][45][46][47].For example, knockdown of PCDHGA9 promoted migration and invasion of gastric cancer cells, while PCDHGA9 overexpression inhibited proliferation and metastasis of gastric cancer cells [43].PCDHGA10 is significantly upregulated in lung squamous cell carcinoma (LUSC) and a high level of PCDHGA10 expression is associated with a poorer prognosis.PCDHGA10 might be a potential molecular marker in LUSC [48].However, the potential role of PCDHGA10 in tumorigenesis of gliomas has not been reported.Therefore, further studies are required to investigate the pathogenic functions of PCDHGA10 in GBM, especially in Chinese population.
Using CNVs analysis, 6 amplification regions and 10 deletion regions were defined as significantly recurrent CNVs.Oncogenes EGFR, FGFR2 and MUC16, as well as tumor-suppressor genes PTEN, MLH1, ATR, and MSH2 were identified according to driver genes in five data sources.EGFR amplification and PTEN deletion have values in diagnosis, response to therapy and prognosis in molecular subgroups of gliomas [49].EGFR amplification occurred in 40-60% of GBM, which may serve as an attractive therapeutic target in GBM [50].Approximately 70% of GBM had PTEN loss [51], however, PTEN loss as a prognostic factor has not been verified and remains controversial [52].EGFR and PTEN could alter receptor tyrosine kinase (RTK)/PI3K/AKT/mTOR pathway and promote tumor progression [53].In our study, LGG had deletions in 1p36.21,2p21 and 2p36.3,whereas amplification in 6p21.33.Notably, 1p36.21 deletion was related to poor prognosis in astrocytoma and neuroblastoma [54,55].
In our study, genomic profiles of gliomas were similar to public databases like TCGA and cBioPortal, such as TP53, IDH1, ATRX, EGFR and PTEN.However, most of gene mutation frequencies were significant differences between our cohort and public databases.Due to different human lineages have genetic heterogeneity, which was shaped by many factors, including evolutionary history, environmental exposures, and lifestyle practices.In addition, the sample size of our cohort was relatively small, which may cause uncertainty frequency counting of gene alterations.
Several limitations should be mentioned in this study.First, the sample size of this retrospective cohort was relatively small.Furthermore, this study was based on single omics, which might lack adequate validation information.In addition, PCDHGA10 might be related to the prognosis of GBM, however, additional experiments are required to explore pathologic functions of PCDHGA10 in gliomas.Hence, we should conduct multi-center studies with larger sample sizes to validate our findings with multi-omics platforms.

Conclusion
This study reveals comprehensive genomic characteristics of LGG and GBM in Chinese patients, which may provide a better understanding of differential molecular signatures between LGG and GBM.In addition, PCDHGA10 mutation might be a novel biomarker for poor prognosis in GBM.The discovery of unique molecular biomarkers could contribute to glioma classification, help predict prognosis and provide therapeutic options.These results need to be confirmed by comprehensive studies with larger sample sizes, especially for a prognostic role of PCDGHA10 in GBM.

Fig 5 .
Fig 5.The frequencies of oncogenic signaling pathways altered in patients with gliomas.(A) The frequencies of oncogenic signaling pathways altered in gliomas.(B) RTK/RAS pathway.(C) PI3K pathway.(D) HIPPO pathway.(E) NOTCH pathway.Pathways were labeled with LGG on the left whereas GBM on the right.Red represents an oncogene while blue represents a tumor suppressor gene.https://doi.org/10.1371/journal.pone.0309536.g005

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